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Showing 1 to 11 of 11 for “"augmented Lagrangian method"”.

  1. Bregman Augmented Lagrangian Method: Convergence, acceleration, and applications in reinforcement learning

    … thesis, the algorithm Bergman proximal point method (BPP), and its application to Bregman augmented Lagrangian method(BALM) is considered. Unlike classical augmented Lagrangian method (ALM ), whose convergence rate and its relation with the proximal point method is well-understood, the …

    uiuc Repository record for Bregman Augmented Lagrangian Method: Convergence, acceleration, and applications in reinforcement learning (opens in a new tab)

  2. A New Node-to-Node Approach to Contact/impact Problems for Two Dimensional Elastic Solids Subject to Finite Deformation

    … is incorporated as the contact constraint. The augmented Lagrangian method is primarily used to apply contact constraints. Non-classical Coulomb friction laws are used where friction is present. Several quasi-static and impact examples are given to demonstrate the performance and validity of the …

    uiuc Repository record for A New Node-to-Node Approach to Contact/impact Problems for Two Dimensional Elastic Solids Subject to Finite Deformation (opens in a new tab)

  3. Constrained Optimization on SO(3), via Pseudospectral Collocation

    … is a widely used direct transcription method that discretizes continuous systems with spectral accuracy and high fidelity while requiring relatively few collocation points. The special orthogonal group, SO(3), is both a Lie group and a manifold, and thus demands on-manifold optimization …

    embry-riddle Repository record for Constrained Optimization on SO(3), via Pseudospectral Collocation (opens in a new tab)

  4. Low rank methods for optimizing clustering

    … variables, and can be locally optimized using an augmented Lagrangian method. In addition, we consider two fast multiplier methods to accelerate the convergence of the augmented Lagrangian scheme: a proximal method of multipliers and an alternating direction method of multipliers. For the proximal …

    purdue-thes Repository record for Low rank methods for optimizing clustering (opens in a new tab)

  5. Optimization Algorithms for Structured Machine Learning and Image Processing Problems

    … and interpret the data. Traditional optimization methods, such as the interior-point method, can solve a wide array of problems arising from the machine learning domain, but it is also this generality that often prevents them from dealing with large data efficiently. Hence, specialized algorithms …

    columbia-diss Repository record for Optimization Algorithms for Structured Machine Learning and Image Processing Problems (opens in a new tab)

  6. Multidisciplinary design of thermally radiating structures using a level set based topology optimization approach

    … While multidisciplinary structural optimization methods have been employed to design these systems, few have incorporated thermal radiation as part of their multi-physics analysis capability. Moreover, with the rapid advancement of manufacturing technologies, the ability to fabricate flight …

    mit Repository record for Multidisciplinary design of thermally radiating structures using a level set based topology optimization approach (opens in a new tab)

  7. Machine learning models for reliable airline ancillary pricing

    … the derivatives. We further present an Augmented Lagrangian Method (ALM) to solve this constrained optimization problem. Experiments on three real-world datasets illustrate that even though both PenDer and state-of-the-art Lattice models achieve similar conformance to shape, PenDer …

    uiuc Repository record for Machine learning models for reliable airline ancillary pricing (opens in a new tab)

  8. Exterior Penalty Approaches for Solving Linear Programming Problems

    … for solving linear programming problems. These methods are an active set l2 penalty approach (ASL2), an inequality-equality based l2 penalty approach (IEL2), and an augmented Lagrangian approach (ALAG). Particular effective variants are presented for each method, along with comments and …

    vt Repository record for Exterior Penalty Approaches for Solving Linear Programming Problems (opens in a new tab)

  9. Modeling and Development of Iterative Reconstruction Algorithms in Emerging X-ray Imaging Technologies

    … associated with use of analytic reconstruction methods in DPCT, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction. Secondly, to improve image quality in grating-based phase-contrast tomography, we …

    wustl Repository record for Modeling and Development of Iterative Reconstruction Algorithms in Emerging X-ray Imaging Technologies (opens in a new tab)

  10. Distributed Optimization Algorithms for Networked Systems

    <p>Distributed optimization methods allow us to decompose an optimization problem</p><p>into smaller, more manageable subproblems that are solved in parallel. For this</p><p>reason, they are widely used to solve large-scale problems arising in areas as diverse</p><p>as wireless communications, …

    duke Repository record for Distributed Optimization Algorithms for Networked Systems (opens in a new tab)

  11. Direct numerical simulation of viscoplastic particulate flows

    … field. In this work we adopt the overset grid method, allowing each particle to be explicitly represented with a curvilinear grid, thereby enabling cost-effective resolution of boundary layer flows. Secondly, the governing equations of viscoplatic fluid flow are non-linear, even in the absence …

    cambridge Repository record for Direct numerical simulation of viscoplastic particulate flows (opens in a new tab)